Why Use AI?
The best decisions made in any business or organisation are those that are supported by analysis of the data that the company has at its disposal. In most cases, an average business may only ever analyse 10-20% of its data, whether this be sales figures, customer habits, demographic or geographic trends. This is usually because an entire organisation’s data is vast and the compute power and time to achieve more than 20% is too time consuming or costly.
Greater analysis of the data within your organisation allows you to understand what parameters drive your success, or cause you issues - the deeper you analyse the more insight you get and the better decisions, changes and improvements you can make.
Moving to a Data Driven Business Model
The rise of GPU technology delivering hugely parallel compute power and the growth in available data has led to the ability to analyse the majority or even all of an organisation’s data - but crucially in much shorter timeframes than ever before. The huge range of GPU products on the market now enable even a single workstation to add value by rapidly analysing datasets, and with larger budgets the sky is the limit when it comes to GPU-accelerated datacentres. This is why the use of AI and deep learning technologies is in exponential growth within every sector. Read on to select you sector.
Implementing AI Solutions for every industry
An ever-increasing number of businesses are turning to deep learning and AI to solve their greatest challenges, beat the competition and deliver the best solutions to their customers. Whether optimising operations with powerful and fast analytics solutions, enabling more accurate faster diagnoses in healthcare, delivering personalised customer experiences in retail, when powerful AI-driven platforms are integrated into existing workflows, business is improved and industry is transformed. The possibilities are endless - select the industry of interest below, to learn about how AI is being used today, and discover real world case studies.
Case Studies
EnvirometriX and OpenGeoHub
Learn how OpenGeoHub and EnvirometriX pioneered a global predictive vegetation and soil mapping system using AI technology.
Read moreAI for the Energy Industry
Energy touches every aspect of modern society, from our personal lives to impacting world economies. Today, the industry faces challenges in exploring new resources, reducing costs, maintaining safe conditions for workers and communities, and ensuring reliable energy delivery to customers. There are numerous ways that GPU-accelerated systems can help address these challenges including enhancing the performance of complex geophysical and engineering applications to reduce time to results. The high compute power, massively paralleled processors and high-speed memory of GPUs allow oil and gas companies to visualise and analyse petabytes of well location data in milliseconds, implement advanced algorithms to locate faults in underground structure and use deep learning training on raw seismic trace data to accelerate exploration and discover faults in geology.
Protective Health & Environment
Ensure that proper personal protective equipment (PPE) protocols are followed and safety hazards are identified by using AI to observe equipment, predict and detect failures, and save lives.
Predictive Maintenance
Avoid blackouts, downtimes, and unnecessary maintenance costs by identifying discrepancies in machinery in real time and predicting the remaining useful life of equipment. AI offers the visualisation and analysis of massive volumes of production and sensor data such as pump pressures, flow rates, and temperatures.
Inspection
AI models can be deployed to inspect and identify potential problems in hard to reach areas such as oil rig exteriors, high roofing or remote pipelines. Using drones instead of humans not only improves safety but increases accuracy and speed of fault finding.
GPU-accelerated computing for Energy
Not only does GPU-accelerated computing provide the data processing powers to drive real insight, it can also provide the visualisation capabilities to make analysis easy too. The demonstration video uses nearly 300 million well production records from nearly 1.3 million wells, spanning 20 years of well performance, yet offers the chance to analyse production decline performance, correlations, rate of change and compile formation-based type curves in seconds.
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Deep Learning Guide
Now you know how AI and deep learning could help your organisation, why not read on to learn more about the process of deep learning, its terminology, how to prepare your data and where to get started
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